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| ID | Type | Description | Link |
|---|---|---|---|
| R01HL137761 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Heart, Lung, and Blood Institute (NHLBI) | NIH |
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There is a clear need to develop improved tools to stratify risk in patients who seek emergency care for chest pain, one of the most common and potentially deadliest conditions encountered in acute care settings. The ECG has been the mainstay of initial evaluation of chest pain patients, yet is currently only diagnostic for a small subset of patients with ST-elevation myocardial infarction. Prior studies have identified candidate markers of ECG characteristics and preliminary algorithms that can identify patients with non-ST elevation myocardial infarction as well as those with very low risk of coronary artery disease. This study will enroll a cohort of consecutive chest pain patients needed to confirm the accuracy of these ECG markers and determine their maximal clinical utility as part of a risk stratification tool. With these improved tools, emergency providers (physicians, nurses, and paramedics) will be able to streamline the care provided to these patients beyond the costly and time-consuming overnight observation for serial cardiac enzymes and provocative testing.
The disease burden of coronary artery diseases (CAD) remains one of the most serious and persistent health problems for the investigator's nation. One out of every six deaths in the United States is solely attributed to CAD. Every year, nearly 7 million adults visit the emergency department (ED), reporting chest pain associated with a possible heart attack. Being able to immediately differentiate between cardiac (ischemic) and non-cardiac chest pain is crucial and improves survival and reduces disability for thousands of people. The electrocardiogram (ECG) is an indispensable tool to detect ischemia and is the first tool available for initial chest pain evaluation in EDs and, even earlier, by paramedics in the field. Current guidelines focus on ST elevation (STE) to identify patients most in need of immediate treatment. Unfortunately, STE only occurs in one-third of all patients with acute myocardial infarction, and missed myocardial infarction remains one of the highest sources of medical malpractice in emergency medicine. This translates to delayed treatment for nearly 1 million heart attacks until costly, time-consuming, and more invasive diagnostics are conducted and interpreted. Prior work by the investigators has explored novel ECG markers, other than STE, and noted that the dynamic ECG changes in these markers can improve diagnosis of acute coronary syndromes (ACS). This prior data showed that myocardial ischemia disturbs the ventricular repolarization process and results in quantifiable distortions of T waves on the surface 12-lead ECG prior to any displacement of the ST segment. Markers of T wave abnormalities, therefore, can identify patients with ischemic chest pain in the absence of acute ST changes very early in the triage process. The current study plans to evaluate how these novel ischemic ECG changes evolve over time during the acute phase of the coronary syndromes. This approach has a high potential for improving the speed and accuracy of diagnosing ACS and is potentially deployable in any ED or ambulance to greatly accelerate definitive treatment, thereby reducing morbidity and mortality for thousands of patients each year.
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| Measure | Description | Time Frame |
|---|---|---|
| Acute Coronary Syndrome (ACS) | The presence of symptoms of ischemia (i.e. diffuse discomfort in the chest, upper extremity, jaw, or epigastric area for more than 20 minutes) and at least one of the following criteria: (1) subsequent development of labile, ischemic ECG changes (e.g., ST changes, T inversion) during hospitalization, (2) elevation of cardiac troponin (i.e., > 99th percentile) during hospital stay, (3) coronary angiography demonstrating greater than 70% stenosis, with or without treatment, and/or (4) functional cardiac evaluation (stress testing) that demonstrates ECG, echocardiographic, or radionuclide evidence of focal cardiac ischemia. | within 30 days of indexed admission |
| Occlusion Myocardial Infarction (OMI) | Coronary angiographic evidence of an acute culprit lesion in at least one of the three main coronary arteries (left anterior descending, left circumflex, right coronary artery) or their primary branches with TIMI flow grade of 0-1. TIMI flow grade of 2 with significant coronary narrowing > 70% and peak troponin of 5-10.0 ng/mL is also considered indicative of OMI. | during index admission |
| Major Adverse Cardiac Events (MACE) | A composite endpoint of 1) all-cause death, 2) resuscitated or fatal cardiac arrest; 3) post-admission pulmonary embolus; 4) ventricular arrhythmia; 5) cardiogenic shock; and 6) acute heart failure (new) or acute exacerbation of chronic heart failure. | Within 30 days of indexed admission |
| Measure | Description | Time Frame |
|---|---|---|
| Cardiovascular Death | Death within 30 days of initial presentation due to any CV-related etiology ( ICD-9 codes 390-459). Thirty-day re-infarction or life-threatening ventricular arrhythmias (VT/VF) requiring cardioversion will be considered CV-death equivalent. Unexplained deaths occurring within 30 days of indexed event will be considered CV-related. | Within 30 days of indexed admission |
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Inclusion Criteria:
Exclusion Criteria:
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The proposed study is a prospective observational cohort study that will include consecutive patients in Pittsburgh, PA who call 9-1-1 with a chief complaint of chest pain.
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| Name | Affiliation | Role |
|---|---|---|
| Salah s Al-Zaiti, RN, PhD | Univ of Pittsburgh | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Pittsburgh Medical Center | Pittsburgh | Pennsylvania | 15213 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36253296 | Derived | Bouzid Z, Faramand Z, Martin-Gill C, Sereika SM, Callaway CW, Saba S, Gregg R, Badilini F, Sejdic E, Al-Zaiti SS. Incorporation of Serial 12-Lead Electrocardiogram With Machine Learning to Augment the Out-of-Hospital Diagnosis of Non-ST Elevation Acute Coronary Syndrome. Ann Emerg Med. 2023 Jan;81(1):57-69. doi: 10.1016/j.annemergmed.2022.08.005. Epub 2022 Oct 15. | |
| 34465465 | Derived | Faramand Z, Helman S, Ahmad A, Martin-Gill C, Callaway C, Saba S, Gregg RE, Wang J, Al-Zaiti S. Performance and limitations of automated ECG interpretation statements in patients with suspected acute coronary syndrome. J Electrocardiol. 2021 Nov-Dec;69S:45-50. doi: 10.1016/j.jelectrocard.2021.08.014. Epub 2021 Aug 18. |
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| ID | Term |
|---|---|
| D002637 | Chest Pain |
| D009203 | Myocardial Infarction |
| D017202 | Myocardial Ischemia |
| D054058 | Acute Coronary Syndrome |
| ID | Term |
|---|---|
| D010146 | Pain |
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| 33494961 | Derived | Faramand Z, Martin-Gill C, Callaway C, Al-Zaiti S. Modified HEART score to optimize risk stratification in cocaine-associated chest pain. Am J Emerg Med. 2021 Sep;47:307-308. doi: 10.1016/j.ajem.2021.01.023. Epub 2021 Jan 15. No abstract available. |
| 33459029 | Derived | Bouzid Z, Faramand Z, Gregg RE, Frisch SO, Martin-Gill C, Saba S, Callaway C, Sejdic E, Al-Zaiti S. In Search of an Optimal Subset of ECG Features to Augment the Diagnosis of Acute Coronary Syndrome at the Emergency Department. J Am Heart Assoc. 2021 Feb 2;10(3):e017871. doi: 10.1161/JAHA.120.017871. Epub 2021 Jan 17. |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D014652 | Vascular Diseases |
| D007238 | Infarction |
| D007511 | Ischemia |
| D010335 | Pathologic Processes |
| D009336 | Necrosis |